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Record W1991902364 · doi:10.1080/17457300.2011.635207

Associations of traffic safety attitudes and ticket fixing behaviours with the crash history of Pakistani drivers

2011· article· en· W1991902364 on OpenAlexaff
Mohsin Durrani, Hunniya Waseem, Junaid A. Bhatti, Junaid Razzak, Rizwan Naseer

Bibliographic record

VenueInternational Journal of Injury Control and Safety Promotion · 2011
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsCrashTicketPoison controlConfidence intervalInjury preventionOccupational safety and healthEnforcementOdds ratioOddsTransport engineeringDemographyMedicineComputer securityEngineeringLogistic regressionEnvironmental healthPolitical scienceSociologyComputer scienceLaw

Abstract

fetched live from OpenAlex

The study assessed whether traffic safety attitudes and ticket fixing behaviours were associated with the crash history. A total of 4018 male drivers from Lahore city participated in this cross sectional study. Most were aged 18-30 years (58.7%, n = 2362), 71.9% (n = 2887) received a traffic ticket, 66.5% (n = 2672) reported previous traffic ticket fixing and 71.3% (n = 2865) considered crashes as being the will of God. Crash history was reported by 95.4% (n = 3821) of drivers, and 58.2% of them reported being involved in a road traffic crash. The likelihood of reporting a previous crash was higher in those who had received a traffic sign violation ticket [adjusted odds ratio (aOR) = 1.40; 95% confidence interval (95%CI) = 1.15-1.72], were involved in traffic ticket fixing (aOR = 1.28; 95%CI = 1.07-1.53), and considered crashes as will of God (aOR = 1.86; 95% CI = 1.57-2.22). These results suggested the need for improving traffic enforcement monitoring and safety education in Pakistan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.218
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Injury Control and Safety PromotionSame topicTraffic and Road SafetyFrench-language works237,207